Optimal DNA pooling-based two-stage designs in case-control association studies.
Study cost remains the major limiting factor for genome-wide association studies due to the necessity of genotyping a large number of SNPs for a large number of subjects. Both DNA pooling strategies and two-stage designs have been proposed to reduce genotyping costs. In this study, we propose a cost-effective, two-stage approach with a DNA pooling strategy. During stage I, all markers are evaluated on a subset of individuals using DNA pooling. The most promising set of markers is then evaluated with individual genotyping for all individuals during stage II. The goal is to determine the optimal parameters (pi(p)(sample ), the proportion of samples used during stage I with DNA pooling; and pi(p)(marker ), the proportion of markers evaluated during stage II with individual genotyping) that minimize the cost of a two-stage DNA pooling design while maintaining a desired overall significance level and achieving a level of power similar to that of a one-stage individual genotyping design. We considered the effects of three factors on optimal two-stage DNA pooling designs. Our results suggest that, under most scenarios considered, the optimal two-stage DNA pooling design may be much more cost-effective than the optimal two-stage individual genotyping design, which use individual genotyping during both stages.
Zhao
Yihong
Y
Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, N.Y., USA.
Wang
Shuang
S
D016022:Case-Control Studies; D003362:Cost-Benefit Analysis; D004247:DNA / Q000235:genetics*; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D015894:Genome, Human; D055106:Genome-Wide Association Study / Q000191:economics / Q000706:statistics & numerical data; D005838:Genotype; D006801:Humans; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis / Q000191:economics / Q000706:statistics & numerical data; D012107:Research Design
D005819:Genetic Markers; D004247:DNA